Academic literature on the topic 'Multiscale Entropy'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Multiscale Entropy.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Multiscale Entropy"
1
Starck, J. L., and F. Murtagh. "Multiscale entropy filtering." Signal Processing 76, no. 2 (July 1999): 147–65. http://dx.doi.org/10.1016/s0165-1684(99)00005-5.
Full text
2
BAR-YAM, Y. "MULTISCALE COMPLEXITY/ENTROPY." Advances in Complex Systems 07, no. 01 (March 2004): 47–63. http://dx.doi.org/10.1142/s0219525904000068.
Full textAbstract:
We discuss the role of scale dependence of entropy/complexity and its relationship to component interdependence. The complexity as a function of scale of observation is expressed in terms of subsystem entropies for a system having a description in terms of variables that have the same a priori scale. The sum of the complexity over all scales is the same for any system with the same number of underlying degrees of freedom (variables), even though the complexity at specific scales differs due to the organization/interdependence of these degrees of freedom. This reflects a tradeoff of complexity at different scales of observation. Calculation of this complexity for a simple frustrated system reveals that it is possible for the complexity to be negative. This is consistent with the possibility that observations of a system that include some errors may actually cause, on average, negative knowledge, i.e. incorrect expectations.
3
Xu, Fan, Peter Wai Tat TSE, Yan-Jun Fang, and Jia-Qi Liang. "A fault diagnosis method combined with compound multiscale permutation entropy and particle swarm optimization–support vector machine for roller bearings diagnosis." Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology 233, no. 4 (July 20, 2018): 615–27. http://dx.doi.org/10.1177/1350650118788929.
Full textAbstract:
A method based on compound multiscale permutation entropy, support vector machine, and particle swarm optimization for roller bearings fault diagnosis was presented in this study. Firstly, the roller bearings vibration signals under different conditions were decomposed into permutation entropy values by the multiscale permutation entropy and compound multiscale permutation entropy methods. The compound multiscale permutation entropy model combined the different graining sequence information under each scale factor. The average value of each scale factor was regarded as the final entropy value in the compound multiscale permutation entropy model. The compound multiscale permutation entropy model suppressed the shortcomings of poor stability caused by the length of the original signals in the multiscale permutation entropy model. Validity and accuracy are considered in the numerical experiments, and then compared with the computational efficiency of the multiscale permutation entropy method. Secondly, the entropy values of the multiscale permutation entropy/compound multiscale permutation entropy under different scales are regarded as the input of the particle swarm optimization–support vector machine models for fulfilling the fault identification, the classification accuracy is used to verify the effectiveness of the multiscale permutation entropy/compound multiscale permutation entropy with particle swarm optimization–support vector machine. Finally, the experimental results show that the classification accuracy of the compound multiscale permutation entropy model is higher than that of the multiscale permutation entropy.
4
Ahmed, Mosabber Uddin, and Danilo P. Mandic. "Multivariate Multiscale Entropy Analysis." IEEE Signal Processing Letters 19, no. 2 (February 2012): 91–94. http://dx.doi.org/10.1109/lsp.2011.2180713.
Full text
5
Humeau-Heurtier, Anne, Chiu-Wen Wu, and Shuen-De Wu. "Refined Composite Multiscale Permutation Entropy to Overcome Multiscale Permutation Entropy Length Dependence." IEEE Signal Processing Letters 22, no. 12 (December 2015): 2364–67. http://dx.doi.org/10.1109/lsp.2015.2482603.
Full text
6
Grmela, Miroslav, Michal Pavelka, Václav Klika, Bing-Yang Cao, and Nie Bendian. "Entropy and Entropy Production in Multiscale Dynamics." Journal of Non-Equilibrium Thermodynamics 44, no. 3 (July 26, 2019): 217–33. http://dx.doi.org/10.1515/jnet-2018-0059.
Full textAbstract:
Abstract Heat conduction is investigated on three levels: equilibrium, Fourier, and Cattaneo. The Fourier level is either the point of departure for investigating the approach to equilibrium or the final stage in the investigation of the approach from the Cattaneo level. Both investigations bring to the Fourier level an entropy and a thermodynamics. In the absence of external and internal influences preventing the approach to equilibrium the entropy that arises in the latter investigation is the production of the classical entropy that arises in the former investigation. If the approach to equilibrium is prevented, then the entropy that arises in the investigation of the approach from the Cattaneo level to the Fourier level still brings to the Fourier level the entropy and the thermodynamics even if the classical entropy and the classical thermodynamics are absent. We also note that vanishing total entropy production as a characterization of equilibrium state is insufficient.
7
Li Peng, Liu Cheng-Yu, Li Li-Ping, Ji Li-Zhen, Yu Shou-Yuan, and Liu Chang-Chun. "Multiscale multivariate fuzzy entropy analysis." Acta Physica Sinica 62, no. 12 (2013): 120512. http://dx.doi.org/10.7498/aps.62.120512.
Full text
8
Starck, Jean-Luc, and Eric Pantin. "Multiscale maximum entropy images restoration." Vistas in Astronomy 40, no. 4 (January 1996): 563–69. http://dx.doi.org/10.1016/s0083-6656(96)00042-6.
Full text
9
Humeau-Heurtier, Anne. "Multivariate Generalized Multiscale Entropy Analysis." Entropy 18, no. 11 (November 17, 2016): 411. http://dx.doi.org/10.3390/e18110411.
Full text
10
Wang, Xianzhi, Shubin Si, Yongbo Li, and Xiaoqiang Du. "An integrated method based on refined composite multivariate hierarchical permutation entropy and random forest and its application in rotating machinery." Journal of Vibration and Control 26, no. 3-4 (November 5, 2019): 146–60. http://dx.doi.org/10.1177/1077546319877711.
Full textAbstract:
Fault feature extraction of rotating machinery is crucial and challenging due to its nonlinear and nonstationary characteristics. In order to resolve this difficulty, a quality nonlinear fault feature extraction method is required. Hierarchical permutation entropy has been proven to be a promising nonlinear feature extraction method for fault diagnosis of rotating machinery. Compared with multiscale permutation entropy, hierarchical permutation entropy considers the fault information hidden in both high frequency and low frequency components. However, hierarchical permutation entropy still has some shortcomings, such as poor statistical stability for short time series and inability of analyzing multichannel signals. To address such disadvantages, this paper proposes a new entropy method, called refined composite multivariate hierarchical permutation entropy. Refined composite multivariate hierarchical permutation entropy can extract rich fault information hidden in multichannel signals synchronously. Based on refined composite multivariate hierarchical permutation entropy and random forest, a novel fault diagnosis framework is proposed in this paper. The effectiveness of the proposed method is validated using experimental and simulated signals. The results demonstrate that the proposed method outperforms multivariate multiscale fuzzy entropy, refined composite multivariate multiscale fuzzy entropy, multivariate multiscale sample entropy, multivariate multiscale permutation entropy, multivariate hierarchical permutation entropy, and composite multivariate hierarchical permutation entropy in recognizing the different faults of rotating machinery.
Dissertations / Theses on the topic "Multiscale Entropy"
1
Granero, Belinchon Carlos. "Multiscale Information Transfer in Turbulence." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEN040/document.
Full textAbstract:
Cette thèse est consacrée à l’étude statistique des systèmes complexes à travers l’analyse de signaux expérimentaux, de signaux synthétiques et de signaux générés à partir de modèles théoriques. On a choisi la turbulence comme paradigme d’ ́etude en raison de ses propriétés: dynamique non linéaire, comportement multi-échelle, cascade d’énergie, intermittence ... Afin de faire une caractérisation statistique d’un système complexe on s’intéresse à l’étude de la distribution (fonction de densité de probabilité), des corrélations et dépendances, et des relations de causalité de Wiener, des signaux qui décrivent le système. La théorie de l’information apparaît comme un cadre idéal pour developer ce type d’analyse. Dans le cadre de la théorie de l’information on a développé deux méthodologies, différentes mais reliées, pour analyser les propriétés d’auto similarité d’un système complexe, et plus précisément de la turbulence. La première méthodologie est basée sur l’analyse des incréments du processus étudié, avec l’entropie de Shannon et la divergence de Kullback-Leibler. La deuxième méthode, qui permet d’analyser des processus non stationnaires, est basée sur l’analyse du processus avec le taux d’entropie de Shannon. On a étudié la relation entre les deux méthodologies, lesquelles caractérisent la distribution d’information du système et la déformation de la distribution des incréments, à travers les échellesMost of the time when studying a system, scientists face processes whose properties are a priori unknown. Characterising these processes is a major task to describe the studied system. During this thesis, which combines signal processing and physics, we were mainly motivated by the study of complex systems and turbulence, and consequently, we were interested in the study of regularity and self-similarity properties, long range dependence structures and multi-scale behavior. In order to perform this kind of study, we use information theory quantities, which are functions of the probability density function of the analysed process, and so depend on any order statistics of its PDF. We developed different, but related, data analysis methodologies, based on information theory, to analyse a process across scales τ. These scales are usually identified with the sampling parameter of Takens embedding procedure, but also with the size of the increments of the process. The methodologies developed during this thesis, can be used to characterize stationnary and non-stationnary processes by analysing time windows of length T of the studied signal
2
Pires, Tiago Marques. "Quantificação da complexidade do ritmo cardíaco usando o método da Multiscale Entropy." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/6630.
Full textAbstract:
Dissertação para obtenção do Grau de Mestre em
Engenharia BiomédicaUma forma de aumentar o nosso conhecimento sobre os princípios fundamentais de funcionamento dos sistemas de controlo biológicos é através da análise da dinâmica dos sinais por eles produzidos em condições normais, patológicas e em resposta a estímulos específicos. Porém, a maioria destes sinais desafiam as técnicas tradicionais de processamento de sinal devido a propriedades como a não estacionariedade, não linearidade, irreversibilidade e fractalidade/multi-fractalidade. Várias técnicas inovadoras para avaliar a dinâmica de sinais biológicos foram desenvolvidas na última década. Uma destas técnicas é designada multiscale entropy e quantifica o grau de complexidade de séries temporais. A hipótese subjacente ao trabalho apresentado nesta dissertação de tese de mestrado é a de que a complexidade da dinâmica dos sistemas biológicos se degrada com o envelhecimento e a doença, reflectindo perda de robustez, funcionalidade e capacidade de adaptação. Tal perda pode ocorrer a vários níveis de organização. Neste trabalho focamo-nos na quantificação da complexidade da dinâmica cardíaca de indivíduos normais, novos (50 anos) e mais velhos (>50 anos), e com diferentes graus de insuficiência cardíaca. Os sinais analisados são os dos intervalos de tempo entre batimentos cardíacos sucessivos derivados de registos electrocardiográficos de 24 horas (Holter). As dinâmicas cardíacas durante os períodos diurnos e nocturnos foram quantificadas independentemente. Os resultados anteriormente publicados mostraram que: i) a complexidade da dinâmica cardíaca é máxima para os indivíduos saudáveis e jovens, cujos mecanismos de controlo do ritmo cardíaco estão totalmente intactos; ii) a complexidade da dinâmica cardíaca degrada-se com a idade e ainda mais com a patologia cardíaca. A inovação do trabalho apresentado nesta dissertação reside numa nova implementação do método da multiscale entropy. A ideia subjacente ao método da multiscale entropy é a da quantificação da entropia de uma série temporal em múltiplas escalas de tempo. Vários algoritmos computacionais podem ser utilizados para calcular a entropia. Tanto neste trabalho como no da publicação original do método da multiscale entropy, o algoritmo usado para o cálculo da entropia é o designado sample entropy. Os valores da sample entropy são função de 3 parâmetros: N, m e r. N é o número total de pontos da série temporal; m é o número de componentes dos vectores que são necessários definir-se para o cálculo da sample entropy (tipicamente m = 2); r é um parâmetro usado para avaliar quando é que dois vectores são ou não indiscerníveis. Tipicamente r é igual a 15% do desvio padrão da série temporal. (Se a distância entre ui e uj é inferior ou igual a r, então os dois vectores são considerados indiscerníveis.) Neste trabalho, calculou-se a sample entropy usando um valor r fixo definido tendo por base a taxa de aquisição do electrocardiograma. Esta implementação conduziu a um aumento muito substancial da capacidade de diferenciar as dinâmicas cardíacas dos diferentes grupos de indivíduos.
3
Silva, Luiz Eduardo Virgilio da. "Análise do sinal de variabilidade da frequência cardíaca através de estatística não extensiva: taxa de q-entropia multiescala." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/59/59135/tde-22032013-114045/.
Full textAbstract:
O corpo humano é um sistema complexo composto por vários subsistemas interdependentes, que interagem entre si em várias escalas. Sabe-se que essa complexidade fisiológica tende a diminuir com a presença de doenças e com o avanço da idade, reduzindo a capacidade de adaptação dos indivíduos. No sistema cardiovascular, uma das maneira de se avaliar sua dinâmica regulatória é através da análise da variabilidade da frequência cardíaca (VFC). Os métodos clássicos de análise da VFC são baseados em modelos lineares, como é o caso da análise espectral. Contudo, como os mecanismos fisiológicos de regulação cardíaca apresentam características não lineares, as análises utilizando tais modelos podem ser limitadas. Nos últimos tempos, várias propostas de métodos não lineares têm surgido. Porém, não se sabe de uma medida consistente com o conceito de complexidade fisiológica, onde tanto os regimes periódicos como aleatórios são caracterizados como perda de complexidade. Baseado no conceito de complexidade fisiológica, esta tese propõe novos métodos de análise não lineares para séries de VFC. Os métodos consistem da generalização de medidas de entropia já existentes, utilizando a mecânica estatística não aditiva de Tsallis e a técnica de geração de dados substitutos. Foi definido um método, chamado de qSDiff, que calcula a diferença entre a entropia de um sinal e a entropia média de suas séries substitutas. O método de entropia utilizado consiste de uma generalização da entropia amostral (SampEn), utilizando o paradigma não aditivo. Das séries qSDiff foram extraídos três atributos, que foram avaliados como possíveis índices de complexidade fisiológica. A entropia multiescala (MSE) também foi generalizada seguindo o paradigma não aditivo, e os mesmos atributos foram calculados em várias escalas. Os métodos foram aplicados em séries reais de VFC de humanos e de ratos, bem como em um conjunto de sinais simulados, formado por ruídos e mapas, este último em regimes caótico e periódico. O atributo qSDiffmax demonstrou ser consistente para baixas escalas ao passo que os atributos qmax e qzero para escalas maiores, separando e classificando os grupos quanto à complexidade fisiológica. Observou-se ainda uma possível relação entre estes q-atributos com a presença de caos, que precisa ser melhor estudada. Os resultados ainda apontam a possibilidade de que, na insuficiência cardíaca, ocorre maior degradação nos mecanismos de baixa escala, de curto período, ao passo que na fibrilação atrial o prejuízo se estenderia para escalas maiores. As medidas baseadas em entropia propostas são capazes de extrair informações importantes das séries de VFC, sendo mais consistentes com o conceito de complexidade fisiológica do que a SampEn (clássica). Reforçou-se a hipótese de que a complexidade se revela em múltiplas escalas de um sinal. Acreditamos que os métodos propostos podem contribuir bastante na análise da VFC e também de outros sinais biomédicos.Human body is a complex system composed of several interdependent subsystems, interacting at various scales. It is known that physiological complexity tends to decrease with disease and aging, reducing the adaptative capabilities of the individual. In the cardiovascular system, one way to evaluate its regulatory dynamics is through the analysis of heart rate variability (HRV). Classical methods of HRV analysis are based on linear models, such as spectral analysis. However, as the physiological mechanisms regulating heart rate exhibit nonlinear characteristics, analyzes using such models may be limited. In the last years, several proposals nonlinear methods have emerged. Nevertheless, no one is known to be consistent with the physiological complexity theory, where both periodic and random regimes are characterized as complexity loss. Based on physiological complexity theory, this thesis proposes new methods for nonlinear HRV series analysis. The methods are generalization of existing entropy measures, through Tsallis nonadditive statistical mechanics and surrogate data. We defined a method, called qSDiff, which calculates the difference between the entropy of a signal and its surrogate data average entropy. The entropy method used is a generalization of sample entropy (SampEn), through nonadditive paradigm. From qSDiff we extracted three attributes, which were evaluated as potential physiological complexity indexes. Multiscale entropy (MSE) was also generalized following nonadditive paradigm, and the same attributes were calculated at various scales. The methods were applied to real human and rats HRV series, as well as to a set of simulated signals, consisting of noises and maps, the latter in chaotic and periodic regimes. qSDiffmax attribute proved to be consistent for low scales while qmax and qzero attributes to larger scales, separating and ranking groups in terms of physiological complexity. There was also found a possible relationship between these q-attributes with the presence of chaos, which must be further investigated. The results also suggested the possibility that, in congestive heart failure, degradation occurs rather at small scales or short time mechanisms, while in atrial fibrillation, damage would extend to larger scales. The proposed entropy based measures are able to extract important information of HRV series, being more consistent with physiological complexity theory than SampEn (classical). Results strengthened the hypothesis that complexity is revealed at multiple scales. We believe that the proposed methods can contribute to HRV as well as to other biomedical signals analysis.
4
Raikes, Adam C. "The Effects of Previous Concussions on the Physiological Complexity of Motor Output During a Continuous Isometric Visual-Motor Tracking Task." DigitalCommons@USU, 2017. https://digitalcommons.usu.edu/etd/5803.
Full textAbstract:
The majority of clinical impairments following a concussion resolve within 7-10 days. However, there is limited clarity as to long-term impact of this injury on neurocognitive function, motor control, and particularly integration of these domains. While repetitive head trauma is associated with numerous neurological disorders, the link is not well described. Visual-motor tracking tasks have been used to identify differences in visual processing, error detection, and fine motor control in aging and numerous pathologies. Examining the complexity of motor output from visual-motor tracking provides insight into multiple cognitive and motor function domains, and into fine motor control used for daily living, work, and sport. The purpose of this dissertation was, therefore, to: (1) use multiple regression to determine the extent to which concussion history and symptoms (loss of consciousness and amnesia) influence visual-motor task performance multiscale complexity, and (2) determine whether task performance complexity can distinguish, through logistic regression and prediction, between individuals with and without a history of concussion. In study 1, individuals with (n = 35) and without (n = 15) a history of concussion performed a visual-motor tracking task. Men and women exhibited linear decreases in task performance complexity, as well as midand high-frequency task performance components, with increasing numbers of concussions. However, men and women exhibited differing patterns, as did those with and without a history of concussion-related loss of consciousness. Finally, trial-to-trial complexity variability increased with increasing numbers of concussions. Findings indicate (1) a cumulative reduction in the way in which previously concussed individuals process and integrate visual information to guide behavior and (2) gender is an important consideration in concussion-related visual-motor outcomes. In Study 2, individuals with (n = 85) and without (n = 42) a history of concussion performed a visualmotor tracking task. Linear and nonlinear measures of task performance were used to build gender-specific logistic classification models using 10-fold cross-validation. When ensuring 80% sensitivity, the best models were 75-80% accurate in predicting a history of concussion. Such discrimination has clinical value in identifying individuals who merit further evaluation and observation over time for conditions related to repetitive head traumas.
5
Li, Guanchen. "Non-equilibrium Thermodynamic Approach Based on the Steepest-Entropy-Ascent Framework Applicable across All Temporal and Spatial Scales." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/78354.
Full textAbstract:
In this research, a first-principles, non-equilibrium thermodynamic-ensemble approach applicable across all temporal and spatial scales is developed based on steepest-entropy-ascent quantum thermodynamics (SEAQT). The SEAQT framework provides an equation of motion consisting of both reversible mechanical dynamics and irreversible relaxation dynamics, which is able to describe the evolution of any state of any system, equilibrium or non-equilibrium. Its key feature is that the irreversible dynamics is based on a gradient dynamics in system state space instead of the microscopic mechanics of more traditional approaches. System energy eigenstructure and density operator (or ensemble probability distribution) describe the system and system thermodynamic state, respectively. Extensive properties (i.e., energy, entropy, and particle number) play a key role in formulating the equation of motion and in describing non-equilibrium state evolutions. All the concepts involved in this framework (i.e., eigentstructure, density operator, and extensive properties) are well defined at all temporal and spatial scales leading to the extremely broad applicability of SEAQT.
The focus of the present research is that of developing non-equilibrium thermodynamic models based specifically on the irreversible part of the equation of motion of SEAQT and applying these to the study of pure relaxation processes of systems in non-equilibrium states undergoing chemical reactions and heat and mass diffusion. As part of the theoretical investigation, the new concept of hypo-equilibrium state is introduced and developed. It is able to describe any non-equilibrium state going through a pure relaxation process and is a generalization of the concept of stable equilibrium of equilibrium thermodynamics to the non-equilibrium realm. Using the concept of hypo-equilibrium state, it is shown that non-equilibrium intensive properties can be fundamentally defined throughout the relaxation process. The definition of non-equilibrium intensive properties also relies on various ensemble descriptions of system state. In this research, three SEAQT ensemble descriptions, i.e., the canonical, grand canonical, and isothermal-isobaric, are derived corresponding, respectively, to the definition of temperature, chemical potential, and pressure. To computationally and not just theoretically permit the application of the SEAQT framework across all scales, a density of states method is developed, which is applicable to solving the SEAQT equation of motion for all types of non-equilibrium relaxation processes. In addition, a heterogeneous multiscale method (HMM) algorithm is also applied to extend the application of the SEAQT framework to multiscale modeling. Applications of this framework are given for systems involving chemical kinetics, the heat and mass diffusion of indistinguishable particles, power cycles, and the complex, coupled reaction-diffusion pathways of a solid oxide fuel cell (SOFC) cathode.Ph. D.
6
Davalos, Trevino Antonio. "Sur les Propriétés Statistiques de l'Entropie de Permutation Multi-échelle et ses Raffinements; applications sur les Signaux Électromyographiques de Surface." Thesis, Orléans, 2020. http://www.theses.fr/2020ORLE3102.
Full textAbstract:
L'entropie de permutation (EP) et l'entropie de permutation multi-échelle (EPM) sont largement utilisées dans l'analyse des séries temporelles à la recherche de régularités, notamment dans le contexte du signal biomédical. Les chercheurs doivent trouver des interprétations optimales, qui peuvent être compromises en ne prenant pas en compte les propriétés de l'algorithme MPE, notamment en ce qui concerne ses propriétés statistiques.C'est pourquoi, dans le présent travail, nous développons la théorie statistique qui sous-tend le MPE, notamment en ce qui concerne la caractérisation de ses deux premiers moments dans le contexte de la multi-échelle. Nous explorons ensuite les versions composites de MPE, afin de comprendre les propriétés sous-jacentes à l'amélioration de leurs performances. Nous avons également testé les valeurs attendues du MPE pour les processus stochastiques gaussiens largement utilisés, ce qui permet d'obtenir un repère d'entropie lorsque l'on utilise ces modèles pour simuler des signaux réels. Enfin, nous appliquons les méthodes MPE classique et composite sur des données électromyographiques de surface (sEMG), afin de différencier les différentes dynamiques d'activité musculaire dans les contractions isométriques.À la suite de notre projet, nous avons constaté que l'EPM est une statistique biaisée, qui diminue le respect du facteur multiéchelle indépendamment de la distribution de probabilité des signaux. Nous avons constaté que la variance de la statistique de l'EMM est fortement dépendante de la valeur de l'EMM elle-même, et presque égale à sa limite inférieure de Cramér-Rao, ce qui signifie que c'est un estimateur efficace. Nous avons constaté que les versions composites, bien qu'elles constituent une amélioration, mesurent également des informations réductrices, ce qui modifie l'estimation du PPE. En réponse, nous avons fourni un nouvel algorithme comme alternative à la multi-échelle à gros grains, ce qui améliore encore les estimations.Appliqué à des modèles gaussiens corrélés généraux, nous avons constaté que le MPE était entièrement caractérisé par les paramètres du modèle. Ainsi, nous avons développé une formulation générale de l'EMT attendue pour les dimensions d'encastrement faibles. Lorsque nous l'avons appliqué à des signaux sEMG réels, nous avons été en mesure de distinguer les états de fatigue et de non-fatigue avec toutes les méthodes, en particulier pour les dimensions d'encastrement élevées. En outre, nous avons constaté que la méthode de l'EMT que nous proposons permettait d'améliorer la différence entre les états d'activité.Par conséquent, nous fournissons au lecteur non seulement un développement sur la théorie actuelle du MPE, mais aussi les implications de ces résultats, à la fois dans le contexte de la modélisation et de l'application de ces techniques dans le domaine biomédicalPermutation Entropy (PE) and Multiscale Permutation Entropy (MPE) are extensively used in the analysis of time series searching for regularities, particularly in the context of biomedical signal. The researchers need to find optimal interpretations, which can be compromised by not taking in account the properties of the MPE algorithm, particularly regarding its statistical properties.Therefore, in the present work we expand on the statistical theory behind MPE, particularly regarding to the characterization of its first two moments in the context of multiscaling. We then explore the composite versions of MPE, in order to understand the underlying properties behind their improved performance. We also tested the expected MPE values for widely used Gaussian stochastic processes, which allows to obtain an Entropy benchmark when using these models to simulate real signals. Finally, we apply both the classical and composite MPE methods on surface Electromyographic (sEMG) data, in order to differentiate different muscle activity dynamics in isometric contractions.As a result of our project, we found the MPE to be a biased statistic, which decreases respect to the multiscaling factor regardless of the signals probability distribution. We found the MPE statistic’s variance to be highly dependent to the value of MPE itself, and almost equal to its Cramér-Rao Lower Bound, which means it is an efficient estimator. We found the composite versions, albeit an improvement, also measure reduntant information, which modifies the MPE estimation. In response, we provided a new algorithm as an alternative to the coarse-grain multiscaling, which further improve the estimations.When applied to general correlated Gaussian models, we found the MPE to be completely characterized by the model parameters. Thus, we developed a general formulation for the expected MPE for low embedding dimensions. When we applied to real sEMG signals, we were able to distinguish between fatigue and non-fatigue states with all methods, particularly for high embedding dimensions. Moreover, we found our proposed MPE method to enhance de difference between activity states.Therefore, we provide the reader with not only a development over the current MPE theory, but also with the implications of these findings, both in the context of modelization, and the application of these techniques in the biomedical field
7
Uffreduzzi, Alessio. "Strumentazione mediante sensori inerziali di test per la valutazione delle funzioni visuo-spaziali costruttive in età evolutiva: uno studio preliminare." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017.
Find full textAbstract:
L’obiettivo di questa tesi è quello di indagare la possibilità di strumentare mediante sensori inerziali indossabili alcuni test per la valutazione delle competenze visuo-costruttive: “Salvadanaio” (Posting Coins), “Invertire i pioli” (Turning Pegs) e “Laccio” (Threading Lace) della batteria Movement ABC. A tal fine si è valutata la possibilità di utilizzare parametri quantitativi utilizzati in analisi del movimento per la caratterizzazione della performance dell’arto superiore durante compiti che richiedono appunto abilità visuo-costruttive.
Hanno preso parte allo studio undici soggetti adulti giovani sani e quattro bambini con sviluppo tipico. Dopo aver posizionato i sensori inerziali sui polsi è stato richiesto ai soggetti di svolgere i test sopraelencati come da manuale di riferimento. Da questo studio preliminare, i parametri che sono risultati più rilevanti per la caratterizzazione delle abilità visuo-costruttive sono stati la complessità (misurata con la Multiscale Entropy) e la frequenza mediana, stimate sul segnale accelerometrico dell’arto che eseguiva l’esercizio. Questi parametri hanno mostrato, come atteso, un trend diverso tra soggetti adulti e quelli in età evolutiva. I risultati di questo studio potranno essere utilizzati come base di partenza per ulteriori sviluppi futuri.
8
SILVA, José Rodrigo Santos. "Avaliação de autocorrelações e complexidade de séries temporais climáticas no Brasil." Universidade Federal Rural de Pernambuco, 2014. http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5009.
Full textAbstract:
Submitted by (ana.araujo@ufrpe.br) on 2016-07-07T11:52:38Z
No. of bitstreams: 1
Jose Rodrigo Santos Silva.pdf: 13129069 bytes, checksum: b427ff42ec7918c3d0cf7f63798ed648 (MD5)Made available in DSpace on 2016-07-07T11:52:38Z (GMT). No. of bitstreams: 1 Jose Rodrigo Santos Silva.pdf: 13129069 bytes, checksum: b427ff42ec7918c3d0cf7f63798ed648 (MD5) Previous issue date: 2014-09-19
The objective of this study was to uncloak the dynamic of climate of Brazil, seeking to measure the regularity and the long range autocorrelation of daily climate series of temperature of air (average, maximum, minimum, and temperature range), relative humidity of air average and wind speed average. The data were obtained by Instituto Nacional de Meteorologia (INMET), at 264 meteorological stations, in the period from January 1990 to December 2012. We use the Detrended Fluctuation Analysis to realize the estimation of the Hurst exponent, the Multiscale Sample Entropy to estimating the entropy of series and the Kriging to interpolate the estimates made. We observed that higher latitudes tend to attenuate the mean of temperatures of air maximum, minimum and average, but increase the variability of the same. This inversion of the magnitudes of the mean and standard deviation is also observed in the relative humidity of air. The means of the estimated Hurst exponents estimated for Brazil were 0.81, 0.79, 0.81, 0.77, 0.83 and 0.64, and the estimated Sample Entropy, 1.39, 1.78, 1.46, 1.41, 1.56 and 1.66, respectively for average, maximum and minimum temperatures of air, temperature range, relative humidity of air average and wind speed average. The values of the estimated Hurst exponents showed a positive correlation with latitude in the temperature variables studied. Such a correlation was not observed in other variables. This a correlation was not observed in other variables. The regularities of climate series in Brazil were medians. Spatially, the greatest changes occurred in estimates of entropies in the scale 1 to 2 of , in the Multiscale Sample Entropy. As from ≥2 the changes observed were more subtle. We observe the influence of the Equatorial Continental air mass in entropy of temperatures daily average and maximum of air. The climatic factor of altitude influenced with more frequently in the observed results, mainly on temperature variables. In some cases, the continentality and the air masses were also identified as important factors in characterizing the spatial distribution of estimates made.
O objetivo deste estudo foi desvendar a dinâmica climática do Brasil, buscando mensurar a regularidade e a autocorrelação de longo alcance em séries climáticas diárias de temperatura do ar (média, máxima, mínima, e amplitude térmica), umidade relativa média do ar e velocidade média diária do vento. Os dados foram obtidos pelo Instituto Nacional de Meteorologia, em 264 estações meteorológicas, no período de janeiro de 1990 a dezembro de 2012. Utilizamos o Detrended Fluctuation Analysis para realizar a estimativa do expoente de Hurst, o Multiscale Sample Entropy para as estimativas da entropia das séries e o Kriging para a interpolação das estimativas realizadas. Observamos que maiores latitudes tendem a atenuar as médias das temperaturas máxima, mínima e média do ar, porém aumentam a variabilidade das mesmas. Esta inversão entre as magnitudes da média e do desvio padrão também é observado na umidade relativa média do ar. As médias dos expoentes de Hurst estimados para todo o Brasil foram 0,81; 0,79; 0,81; 0,77; 0,83 e 0,64; e do Sample Entropy estimado, 1,39; 1,78; 1,46; 1,41; 1,56 e 1,66, respectivamente para séries diárias de temperatura média, máxima e mínima do ar, amplitude térmica do ar, umidade relativa média do ar e velocidade média do vento. Os valores do expoentes de Hurst estimados apresentaram uma correlação positiva com a latitude nas variáveis de temperatura do ar estudadas. Tal correlação não foi observada nas demais variáveis. As regularidades das séries climáticas no Brasil foram medianas. Espacialmente, as maiores alterações nas estimativas das entropias ocorreram na escala 1 para a 2 de , no Multiscale Sample Entropy. A partir de ≥2 as mudanças observadas foram mais sutis. Observamos influência da massa de ar Equatorial Continental na entropia das temperaturas do ar média e máxima diárias. O fator climático da altitude atuou com maior frequência sob os resultados observados, principalmente nas variáveis de temperatura. Em alguns casos, a continentalidade e as massas de ar também foram apontados como fatores importantes na caracterização da distribuição espacial das estimativas realizadas.
9
Blons, Estelle. "Dynamiques individuelles et collectives de la complexité de signaux physiologiques en situation de stress induit." Thesis, Bordeaux, 2020. http://www.theses.fr/2020BORD0152.
Full textAbstract:
Les études récentes en santé humaine supposent un lien de causalité entre la complexité des systèmes de contrôle psychophysiologique et la complexité des biosignaux qu’ils émettent. Le travail mené dans le cadre de cette thèse illustre ce principe en s’appuyant sur une démarche interdisciplinaire, combinant physiologie, psychologie et traitement du signal. Il vise à étudier les dynamiques des signaux physiologiques émis par l’Homme, en réponse à un stress induit en situation individuelle ou collective. Le stress étant un processus multifactoriel qui dépend de la perception et de l’interprétation d’une situation donnée par un individu, l’étude des signaux physiologiques est combinée à l’évaluation de caractéristiques psychologiques contextuelles et dispositionnelles. En particulier, nous nous intéressons aux régulations cardiaques qui sont analysées à partir des séries temporelles définies par les durées successives des intervalles RR. Des approches statistiques temporelles, fréquentielles ou non-linéaires sont utilisées afin d’étudier les capacités d’adaptation des individus confrontés à différentes situations de tâches cognitives associées ou non à des facteurs stressants. Il s’agit d’extraire des signatures caractéristiques des régulations centrales et autonomes, au repos ou dans différentes situations expérimentales. Dans ce travail, un intérêt particulier est accordé à l’entropie multi-échelles afin d’évaluer la complexité des signaux, une complexité induite par les interconnexions existant entre structures corticales, sous-corticales et régulations autonomes cardiaques. Nous proposons également d’analyser les signaux collectés durant les différentes situations expérimentales, en comparant deux à deux leurs densités de probabilité à partir de la divergence de Kullback-Leibler, et en particulier d’une estimation de l'incrément asymptotique de la divergence de Kullback-Leibler. Les résultats obtenus mettent en évidence que l’étude des signaux cardiaques peut permettre d’appréhender l’état psychophysiologique d’un individu lorsqu’il est confronté à des situations de tâches cognitives et de stress. Des différences d’états apparaissent non seulement à l’échelle individuelle, mais également à l’échelle collective, lorsque l’individu n’est pas directement confronté aux stimuli stressants mais que le stress est de nature empathique. Enfin, deux applications sont réalisées. Nous montrons que la complexité des signaux cardiaques, altérée chez des personnes stressées au travail, peut être améliorée par un entraînement à la cohérence cardiaque. Nous appliquons également les méthodes de traitement du signal à l’étude de la régulation posturale. L’ensemble de nos résultats renforcent l’intérêt du monitoring de l’humain en matière de santéRecent studies in human health assume a causal link between the complexity of psychophysiological control systems and the complexity of their resulting biosignals. This PhD illustrates the aforementioned principle by relying on an interdisciplinary approach, combining physiology, psychology and signal processing. The dynamics of human output physiological signals are studied in response to induced stress in individual or collective situations. The objective is to extract individual signatures depicting the central and autonomic regulations at rest or in different experimental situations. Since stress is a multifactorial process depending on the individual perception and interpretation of a situation, the study of physiological signals is combined with the evaluation of psychological contextual and dispositional characteristics. We focus our attention on cardiac regulations which are analysed from the time series defined by the successive durations of the RR intervals. Statistical signal processing methods, either temporal, frequency or non-linear, are used to study the adaptive capacities of individuals facing different situations of cognitive tasks associated or not with stressors. A particular interest is given to multiscale entropy to assess the complexity of signals, which makes it possible to consider the interconnections existing between cortical, subcortical structures and autonomic cardiac regulations. The probability density functions of recorded cardiac signals along each different experimental situation are compared two by two by using the Kullback-Leibler divergence, and in particular the estimate of the asymptotic increment of the divergence of Kullback-Leibler. The results show that studying cardiac signals allows to discriminate the psychophysiological state of an individual when facing either cognitive tasks or stressful situations. Psychophysiological state differences emerge during stress, not only at an individual level, but also at a collective one, for which the subject is not directly confronted with stressful stimuli. The stress is therefore empathic. Two experimental applications are carried out from our results. First, we show that the cardiac complexity, which is altered in people stressed at work, can be improved by cardiac coherence biofeedback training. Second, signal processing methods are also used to the study of postural regulation. Overall, our results strengthen the interest of human monitoring in health
10
Zhang, Tianyu. "Problème inverse statistique multi-échelle pour l'identification des champs aléatoires de propriétés élastiques." Thesis, Paris Est, 2019. http://www.theses.fr/2019PESC2068.
Full textAbstract:
Dans le cadre de la théorie de l'élasticité linéaire, la modélisation et simulation numérique du comportement mécanique des matériaux hétérogènes à microstructure aléatoire complexe soulèvent de nombreux défis scientifiques à différentes échelles. Bien qu'à l'échelle macroscopique, ces matériaux soient souvent modélisés comme des milieux homogènes et déterministes, ils sont non seulement hétérogènes et aléatoires à l'échelle microscopique, mais ils ne peuvent généralement pas non plus être explicitement décrits par les propriétés morphologiques et mécaniques locales de leurs constituants. Par conséquent, une échelle mésoscopique est introduite entre l'échelle macroscopique et l'échelle mésoscopique, pour laquelle les propriétés mécaniques d'un tel milieu élastique linéaire aléatoire sont décrites par un modèle stochastique prior non-gaussien paramétré par un nombre faible ou modéré d'hyperparamètres inconnus. Afin d'identifier ces hyperparamètres, une méthodologie innovante a été récemment proposée en résolvant un problème statistique inverse multi-échelle en utilisant uniquement des données expérimentales partielles et limitées aux deux échelles macroscopique et mésoscopique. Celui-ci a été formulé comme un problème d'optimisation multi-objectif qui consiste à minimiser une fonction-coût multi-objectif (à valeurs vectorielles) définie par trois indicateurs numériques correspondant à des fonctions-coût mono-objectif (à valeurs scalaires) permettant de quantifier et minimiser des distances entre les données expérimentales multi-échelles mesurées simultanément aux deux échelles macroscopique et mésoscopique sur un seul échantillon soumis à un essai statique, et les solutions des modèles numériques déterministe et stochastique utilisés pour simuler la configuration expérimentale multi-échelle sous incertitudes. Ce travail de recherche vise à contribuer à l'amélioration de la méthodologie d'identification inverse statistique multi-échelle en terme de coût de calcul, de précision et de robustesse en introduisant (i) une fonction-coût mono-objectif (indicateur numérique) supplémentaire à l'échelle mésoscopique quantifiant la distance entre la(les) longueur(s) de corrélation spatiale des champs expérimentaux mesurés et celle(s) des champs numériques calculés, afin que chaque hyperparamètre du modèle stochastique prior ait sa propre fonction-coût mono-objectif dédiée, permettant ainsi d'éviter d'avoir recours à l'algorithme d'optimisation global (algorithme génétique) utilisé précédemment et de le remplacer par un algorithme plus performant en terme d'efficacité numérique, tel qu'un algorithme itératif de type point fixe, pour résoudre le problème d'optimisation multi-objectif avec un coût de calcul plus faible, et (ii) une représentation stochastique ad hoc des hyperparamètres impliqués dans le modèle stochastique prior du champ d'élasticité aléatoire à l'échelle mésoscopique en les modélisant comme des variables aléatoires, pour lesquelles les distributions de probabilité peuvent être construites en utilisant le principe du maximum d'entropie sous un ensemble de contraintes définies par les informations objectives et disponibles, et dont les hyperparamètres peuvent être déterminés à l'aide de la méthode d'estimation du maximum de vraisemblance avec les données disponibles, afin d'améliorer à la fois la robustesse et la précision de la méthode d'identification inverse du modèle stochastique prior. En parallèle, nous proposons également de résoudre le problème d'optimisation multi-objectif en utilisant l’apprentissage automatique par des réseaux de neurones artificiels. Finalement, la méthodologie améliorée est tout d'abord validée sur un matériau virtuel fictif dans le cadre de l'élasticité linéaire en 2D contraintes planes et 3D, puis illustrée sur un matériau biologique hétérogène réel (os cortical de bœuf) en élasticité linéaire 2D contraintes planesWithin the framework of linear elasticity theory, the numerical modeling and simulation of the mechanical behavior of heterogeneous materials with complex random microstructure give rise to many scientific challenges at different scales. Despite that at macroscale such materials are usually modeled as homogeneous and deterministic elastic media, they are not only heterogeneous and random at microscale, but they often also cannot be properly described by the local morphological and mechanical properties of their constituents. Consequently, a mesoscale is introduced between macroscale and microscale, for which the mechanical properties of such a random linear elastic medium are represented by a prior non-Gaussian stochastic model parameterized by a small or moderate number of unknown hyperparameters. In order to identify these hyperparameters, an innovative methodology has been recently proposed by solving a multiscale statistical inverse problem using only partial and limited experimental data at both macroscale and mesoscale. It has been formulated as a multi-objective optimization problem which consists in minimizing a (vector-valued) multi-objective cost function defined by three numerical indicators corresponding to (scalar-valued) single-objective cost functions for quantifying and minimizing distances between multiscale experimental data measured simultaneously at both macroscale and mesoscale on a single specimen subjected to a static test, and the numerical solutions of deterministic and stochastic computational models used for simulating the multiscale experimental test configuration under uncertainties. This research work aims at contributing to the improvement of the multiscale statistical inverse identification method in terms of computational efficiency, accuracy and robustness by introducing (i) an additional mesoscopic numerical indicator allowing the distance between the spatial correlation length(s) of the measured experimental fields and the one(s) of the computed numerical fields to be quantified at mesoscale, so that each hyperparameter of the prior stochastic model has its own dedicated single-objective cost-function, thus allowing the time-consuming global optimization algorithm (genetic algorithm) to be avoided and replaced with a more efficient algorithm, such as the fixed-point iterative algorithm, for solving the underlying multi-objective optimization problem with a lower computational cost, and (ii) an ad hoc stochastic representation of the hyperparameters involved in the prior stochastic model of the random elasticity field at mesoscale by modeling them as random variables, for which the probability distributions can be constructed by using the maximum entropy principle under a set of constraints defined by the available and objective information, and whose hyperparameters can be determined using the maximum likelihood estimation method with the available data, in order to enhance both the robustness and accuracy of the statistical inverse identification method of the prior stochastic model. Meanwhile, we propose as well to solve the multi-objective optimization problem by using machine learning based on artificial neural networks. Finally, the improved methodology is first validated on a fictitious virtual material within the framework of 2D plane stress and 3D linear elasticity theory, and then illustrated on a real heterogenous biological material (beef cortical bone) in 2D plane stress linear elasticity
Books on the topic "Multiscale Entropy"
1
Multiscale Entropy Approaches and Their Applications. MDPI, 2020. http://dx.doi.org/10.3390/books978-3-03943-341-4.
Full textBook chapters on the topic "Multiscale Entropy"
1
Hu, Meng, and Hualou Liang. "Multiscale Entropy: Recent Advances." In Complexity and Nonlinearity in Cardiovascular Signals, 115–38. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58709-7_4.
Full text
2
Nagavi, Trisiladevi C., and Nagappa U. Bhajantri. "Query by Humming System Through Multiscale Music Entropy." In Advances in Intelligent Systems and Computing, 139–50. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2009-1_17.
Full text
3
Boltz, Sylvain, Frank Nielsen, and Stefano Soatto. "Texture Regimes for Entropy-Based Multiscale Image Analysis." In Computer Vision – ECCV 2010, 692–705. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15558-1_50.
Full text
4
Kuo, Chih-En, Sheng-Fu Liang, Yu-Hsuan Shih, and Fu-Zen Shaw. "Evaluating the Sleep Quality Using Multiscale Entropy Analysis." In IFMBE Proceedings, 166–69. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12262-5_46.
Full text
5
Pérez, Patrick, Fabrice Heitz, and Patrick Bouthémy. "Global Bayesian Estimation, Contrained Multiscale Markov Random Fields and the Analysis of Visual Motion." In Maximum Entropy and Bayesian Methods, 383–88. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-017-2217-9_46.
Full text
6
Starck, Jean-Luc, and Eric Pantin. "Astronomical Images Restoration by the Multiscale Maximum Entropy Method." In Statistical Challenges in Modern Astronomy II, 405–6. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-1968-2_29.
Full text
7
Ouyang, Gaoxiang, Chuangyin Dang, and Xiaoli Li. "Complexity Analysis of EEG Data with Multiscale Permutation Entropy." In Advances in Cognitive Neurodynamics (II), 741–45. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9695-1_111.
Full text
8
Deng, Hongxia, Jinxiu Guo, Xiaofeng Yang, Jinxiu Hou, Haoqi Liu, and Haifang Li. "Multiscale Entropy Analysis of EEG Based on Non-uniform Time." In Pattern Recognition and Computer Vision, 3–17. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31723-2_1.
Full text
9
Zhang, Long, Guoliang Xiong, Hesheng Liu, Huijun Zou, and Weizhong Guo. "An Intelligent Fault Diagnosis Method Based on Multiscale Entropy and SVMs." In Advances in Neural Networks – ISNN 2009, 724–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01513-7_79.
Full text
10
Shao, Xuexiao, Bin Hu, Yalin Li, and Xiangwei Zheng. "A Study of Sleep Stages Threshold Based on Multiscale Fuzzy Entropy." In Algorithms and Architectures for Parallel Processing, 239–48. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05057-3_19.
Full textConference papers on the topic "Multiscale Entropy"
1
Starck, Jean-Luc. "Image restoration by multiscale entropy." In SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, edited by Michael A. Unser, Akram Aldroubi, and Andrew F. Laine. SPIE, 1999. http://dx.doi.org/10.1117/12.366843.
Full text
2
Nurwulan, Nurul Retno, and Bernard C. Jiang. "Multiscale Entropy for Physical Activity Recognition." In APIT 2020: 2020 2nd Asia Pacific Information Technology Conference. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3379310.3379318.
Full text
3
Grmela, Miroslav. "Thermodynamics of Reductions in Multiscale Dynamics." In 1st International Electronic Conference on Entropy and Its Applications. Basel, Switzerland: MDPI, 2014. http://dx.doi.org/10.3390/ecea-1-a005.
Full text
4
Ting, Chuan-Wei, and Ching-Yao Wang. "Online multiscale entropy estimation using distribution statistics." In 2012 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2012. http://dx.doi.org/10.1109/icspcc.2012.6335707.
Full text
5
Brockmeier, Austin J., Luis G. Sanchez Giraldo, John S. Choi, Joseph T. Francis, and Jose C. Principe. "Learning multiscale neural metrics via entropy minimization." In 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2013. http://dx.doi.org/10.1109/ner.2013.6695918.
Full text
6
Zhang, Teng, Yu Jin, Shixue Sun, Yinhong Liu, and Xiaohua Douglas Zhang. "Analysis of Impact Factors of Multiscale Entropy." In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2018. http://dx.doi.org/10.1109/bibm.2018.8621400.
Full text
7
Fraiwan, L., and K. Lweesy. "Newborn sleep stage identification using multiscale entropy." In 2014 Middle East Conference on Biomedical Engineering (MECBME). IEEE, 2014. http://dx.doi.org/10.1109/mecbme.2014.6783278.
Full text
8
Pan, Yu-Hsiang, Kun-Hsiung Chang, and Yung-Hung Wang. "Efficient computation of multiscale entropy in biomedicine." In 2010 International Symposium on Computer, Communication, Control and Automation (3CA). IEEE, 2010. http://dx.doi.org/10.1109/3ca.2010.5533753.
Full text
9
Jelinek, Herbert F., David J. Cornforth, Mika P. Tarvainen, and Neboja T. Miloevic. "Multiscale Renyi Entropy and Cardiac Autonomic Neuropathy." In 2015 20th International Conference on Control Systems and Computer Science (CSCS). IEEE, 2015. http://dx.doi.org/10.1109/cscs.2015.148.
Full text
10
Ahmed, Mosabber Uddin, Ling Li, Jianting Cao, and Danilo P. Mandic. "Multivariate multiscale entropy for brain consciousness analysis." In 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. http://dx.doi.org/10.1109/iembs.2011.6090185.
Full text